Las estrategias de enseñanza y las actividades de aprendizaje.…

In this study, the main challenge in data analysis of bioreactor experiments was the variability of the inoculum cell cultures. Due to the limited numbers of bioreactors, it was impossible to perform the experiment of control and SNP treated cultures at the same time. Since the samples were collected batch by batch, the characteristics and composition of polyphenols in the inoculum of cell culture might be different every time. This fact introduced a huge variability in the data which affected the downstream data analysis and statistical modelling, with the results that some polyphenols cannot be modelled as in flask cultures. This fact, highlights the very important point that should be taken into consideration in this type of experiments: to maximize reproducibility, the inoculum should be from the same source of cell cultures. In this case, it can be seen that the data set from the flask cultures are more reproducible.

Scaling-up plant cell cultures from flasks to bioreactor is always a challenging matter that depends on several parameters such as the type of bioreactors, aeration rate, the speed of agitation, supply of nutrients and the size of inoculum etc. (Jeandet et al. 2016). Our study described the successful production of polyphenols in GT cell cultures in stirred-tank bioreactors and the distinct time-course profiles of stilbenes were found in bioreactor cultures as compared to flask cultures.

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Conclusion

The main focus of this thesis was the application of statistical analysis approaches able to compare the ‘trends’ of the different metabolites. In particular, it has been shown how generalized additive models can be used to model the time-dependent profile of secondary metabolites in grapevine cell suspension cultures, following treatment with methyl jasmonate and sodium nitroprusside. Although this type of data analysis strategy has strong potential for the interpretation of the data coming from a wide class of -omic time-resolved experiments, more investigations and statistical methods, such as integration of multi-omics data, need to be made to obtain better understanding of the more complex biological mechanism and to characterize the biochemical interactions of interest organisms.

Appendix

1. Diagnosis plots of GAM models for anthocyanins in VGR cell cultures